Tompkins Adrian M, McCreesh Nicky
Abdus Salam International Centre for Theoretical Physics, Trieste.
Geospat Health. 2016 Mar 31;11(1 Suppl):408. doi: 10.4081/gh.2016.408.
One year of mobile phone location data from Senegal is analysed to determine the characteristics of journeys that result in an overnight stay, and are thus relevant for malaria transmission. Defining the home location of each person as the place of most frequent calls, it is found that approximately 60% of people who spend nights away from home have regular destinations that are repeatedly visited, although only 10% have 3 or more regular destinations. The number of journeys involving overnight stays peaks at a distance of 50 km, although roughly half of such journeys exceed 100 km. Most visits only involve a stay of one or two nights away from home, with just 4% exceeding one week. A new agent-based migration model is introduced, based on a gravity model adapted to represent overnight journeys. Each agent makes journeys involving overnight stays to either regular or random locations, with journey and destination probabilities taken from the mobile phone dataset. Preliminary simulations show that the agent-based model can approximately reproduce the patterns of migration involving overnight stays.
对来自塞内加尔的一年手机定位数据进行分析,以确定导致过夜停留、因而与疟疾传播相关的行程特征。将每个人的家庭住址定义为通话最频繁的地点,结果发现,约60%不在家过夜的人有经常前往的固定目的地,不过只有10%的人有3个或更多固定目的地。涉及过夜停留的行程数量在距离50公里处达到峰值,不过此类行程约有一半超过100公里。大多数外出停留仅为一两个晚上,只有4%超过一周。引入了一种新的基于主体的迁移模型,该模型基于一个经过调整以表示过夜行程的引力模型。每个主体前往固定或随机地点进行过夜停留行程,行程和目的地概率取自手机数据集。初步模拟表明,基于主体的模型能够大致再现涉及过夜停留的迁移模式。